ALCOHOLISM: CLINICAL AND EXPERIMENTAL RESEARCH
Vol. **, No. *
** 2013
Brand-Specific Consumption of Alcohol Among Underage
Youth in the United States
Michael Siegel, William DeJong, Timothy S. Naimi, Erin K. Fortunato, Alison B. Albers,
Timothy Heeren, David L. Rosenbloom, Craig Ross, Joshua Ostroff, Sergei Rodkin,
Charles King, Dina L. G. Borzekowski, Rajiv N. Rimal, Alisa A. Padon, Raimee H. Eck, and
David H. Jernigan
Background: Little is known about brand-specific alcohol consumption among underage youth, as
existing information is collected at the level of alcoholic beverage type. This study identifies the alcohol
brands consumed by a nationally representative sample of underage youth in the United States.
Methods: We obtained a national sample of 1,032 underage youth, aged 13 to 20, using a prerecruited Internet panel maintained by Knowledge Networks. Youth aged 18 to 20 were recruited
directly from the panel via email invitation. Teens aged 13 to 17 were identified by asking adult panelists
to identify a member of their household. The survey assessed the past 30-day consumption of 898
brands of alcohol among 16 alcoholic beverage types, including the frequency and amount of each
brand consumed in the past 30 days. Market share for a given brand was calculated by dividing the
total number of drinks for that brand in the past 30 days across the entire sample by the total number
of drinks for all identified brands.
Results: The alcohol brands with highest prevalence of past 30-day consumption were Bud Light
(27.9%, 95% confidence interval [CI] 23.3 to 32.4%), Smirnoff malt beverages (17.0%, 95% CI 12.9 to
21.1%), and Budweiser (14.6%, 95% CI 11.0 to 18.3%). Brand market share was concentrated in a relatively small number of brands, with the top 25 brands accounting for nearly half of all market shares.
Conclusions: Underage youth alcohol consumption, although spread out over several alcoholic
beverage types, is concentrated among a relatively small number of alcohol brands. This finding has
important implications for alcohol research, practice, and policy.
Key Words: Alcohol, Brand, Underage Drinking, Surveillance, Youth.
U
NDERAGE DRINKING REMAINS a major public
health problem in the United States. More than 70%
of high school students have consumed alcohol, and about
22% engage in heavy episodic drinking (Eaton et al., 2012).
Adequate surveillance of youth alcohol use is essential for
From the Department of Community Health Sciences (MS, WD,
TSN, EKF, ABA), Boston University School of Public Health, Boston,
Massachusetts; Section of General Internal Medicine (TSN), Department of Medicine, Boston University Medical Center, Boston, Massachusetts; Department of Biostatistics (TH), Boston University School of
Public Health, Boston, Massachusetts; Department of Health Policy &
Management (DLR), Boston University School of Public Health,
Boston, Massachusetts; Virtual Media Resources (CR, JO), Natick,
Massachusetts; Knowledge Networks, Inc. (SR), Palo Alto, California;
Pleiades Consulting Group (CK), Lincoln, Massachusetts; Department of
Health, Behavior, and Society (DLGB, RNR, AAP, RHE, DHJ), Johns
Hopkins Bloomberg School of Public Health, Baltimore, Maryland; and
Center on Alcohol Marketing and Youth (DHJ), Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland.
Received for publication October 11, 2012; accepted November 23,
2012.
Reprint requests: Michael Siegel, MD, MPH, Professor, Department
of Community Health Sciences, Boston University School of Public
Health, 801 Massachusetts Avenue, 3rd Floor, Boston, MA 02118; Tel.:
617-638-5167; Fax: 617-638-4483; E-mail: [email protected]
Copyright © 2013 by the Research Society on Alcoholism.
DOI: 10.1111/acer.12084
Alcohol Clin Exp Res, Vol **, No *, 2013: pp 1–9
identifying the causes for youth drinking and planning interventions to prevent its negative consequences. Existing
national surveys of alcohol use among underage youth have
collected data at the level of the alcoholic beverage type
(beer, spirits, wine, etc.), but never at the level of alcohol
brand (Bud Light beer, Grey Goose vodka, Bacardi rum,
etc.) or even liquor subtype (whiskey, rum, tequila, vodka,
etc.). In 2004, in response to the lack of information on
brand-specific youth alcohol use, a National Academy of
Sciences report on alcohol and youth recommended that the
federal government collect alcohol brand preference data
from underage drinkers to determine the influence of alcohol
marketing on youth (Bonnie and O’Connell, 2004). To date,
however, there has been no comprehensive collection or
publication of brand-specific alcohol consumption among
youth at the national level.
Branding plays an essential role in alcohol marketing
and the relationship of youth to individual alcohol products (Casswell, 2004; Gordon et al., 2008; Saffer, 2002).
Developing brand capital—that is, the meaning and emotion associated with a brand—is perhaps the most important function of alcohol advertising (Casswell, 2004;
Gordon et al., 2008). Many adolescents identify with alcohol brands before they start drinking (Aitken et al.,
1988). Even among 10-year-olds, nearly 80% were able to
recognize an alcohol brand logo (Alcohol Concern, 2012).
1
SIEGEL ET AL.
2
Alcohol branding affects youth’s alcohol-related attitudes
(Aitken et al., 1988; Grube and Wallack, 1994), and early
recognition of brands is associated with an increased likelihood of using those brands throughout one’s life (Ellis
et al., 2010). Even so, the scientific literature lacks studies
that explore the link between youth exposure to advertising for specific alcohol brands and their consumption of
those brands. Such studies are not possible unless we first
assess alcohol brand use among underage youth. Being
able to investigate the relationship between underage
drinkers’ preferences for particular brands and their exposure to advertising for those brands would represent a significant advance in alcohol marketing research.
Identifying the brands of alcohol that youth consume
would contribute not only to our knowledge about whether
alcohol advertising affects youth drinking behavior, but also
provide a better understanding of underage drinking behavior itself. First, determining the drinking patterns for specific
brands of alcohol would greatly increase our knowledge of
the factors that influence the initiation and progression of
youth alcohol use.
Second, brand-specific consumption data would allow us
to calculate the total monthly alcohol dose for each specific
type and brand of alcoholic beverage. In particular, it would
allow us to itemize the alcohol brands used by heavy drinkers
and to identify the relationship between the consumption of
those brands and problem drinking, including early signs of
alcohol dependence.
Third, ascertaining youth alcohol use by brand may produce a more accurate description of drinking behavior
among youth. Previous research has established that greater
specificity in asking about alcoholic beverage types results in
higher self-reported consumption (Russell et al., 1991; Serdula et al., 1999). By extension, inquiring about specific alcohol brands could result in an even more accurate assessment
of youth alcohol consumption. Casswell and colleagues
(2002) found that population-based surveys that asked
respondents to report the brands of alcohol they consume
was 1 of the key factors in their ability to account for 94% of
per capita alcohol consumption (as measured by sales data),
compared with <60% in prior surveys (Kerr and Greenfield,
2007; Midanik, 1982). Another reason to ask about specific
brands is that youth may misclassify the brands they consume, leading to inaccurate estimates of drinking prevalence
for alcoholic beverage types such as beer, wine, spirits, and
flavored alcoholic beverages (Giga et al., 2011; Siegel et al.,
2011a). In short, having a complete database of brandspecific alcohol consumption prevalence, including the
frequency and volume of use, would allow us to provide the
most comprehensive description to date of alcohol consumption among youth.
Fourth, identifying the patterns of alcohol brand consumption among youth would help in evaluating the feasibility of including alcohol brand use questions on federal or
national surveys. As was found for cigarettes, if alcohol
brand consumption is concentrated among a relatively small
number of brands, it may be feasible to assess youth alcohol
brand preference in national or federal surveys as only a limited number of brands would need to be included.
Last, monitoring youth alcohol use at the brand level
would provide a mechanism for identifying new entries in the
market that may be popular among youth.
Despite the compelling need for brand-specific alcohol
consumption data among youth, almost all of the previous
surveillance of youth alcohol use has been conducted at the
aggregate level or at the level of alcoholic beverage type.
Several studies have characterized youth drinking patterns
by alcoholic beverage type, including the categories of beer,
malt liquor, liquor, wine, wine coolers, fortified wine, and flavored alcoholic beverages (Cremeens et al., 2009; Maldonado-Molina et al., 2010; Moore and Werch, 2007; Roeber
et al., 2007; Siegel et al., 2011c; Werch et al., 2006).
However, we are only aware of 1 published study that has
reported brand-specific consumption or preferences among
youth (Tanski et al., 2011). Tanski and colleagues (2011)
surveyed a national sample of youth concerning their favorite alcohol brand to drink. Top brand preferences of youth
who engaged in heavy episodic drinking were associated with
brands with high advertising expenditures. This study is a
major research advance, but is limited because it only asked
about each respondent’s favorite brand, not about the full
range of alcohol brands they actually consumed.
One reason why researchers have not collected brandspecific alcohol consumption data is the logistical difficulty
of obtaining consumption information on each of the hundreds of alcohol brands currently in the market. To address
this problem, we developed, pilot-tested, and validated a
novel, Internet-based survey, which measures the consumption prevalence and frequency of hundreds of alcohol brands,
employing a small sample from an Internet panel of nationally representative underage youth (Siegel et al., 2011a,b).
In this article, we report the results of the full-scale administration of this survey to a national sample of underage
youth. We believe this is the first national survey dedicated
to measuring alcohol brand consumption preferences among
underage youth. We report the past 30-day prevalence of
alcohol consumption by brand and the market share by
brand for the overall volume of alcohol consumed in the past
30 days.
MATERIALS AND METHODS
Design Overview
We obtained a sample of 1,032 underage youth, aged 13 to
20, who had consumed at least 1 drink of alcohol in the past
30 days, using a prerecruited Internet panel maintained by
Knowledge Networks (Palo Alto, CA; Knowledge Networks,
2012). Using an online, self-administered survey, we ascertained
each of the brands of alcohol consumed by the respondents during the past 30 days. For each brand, we inquired about the
number of days on which it was consumed and the typical number of drinks of that brand on those days. The primary outcome
variables were the prevalence of 30-day consumption of each
BRAND-SPECIFIC CONSUMPTION OF ALCOHOL
brand and the market share of consumption for each brand (i.e.,
the proportion of all drinks of alcohol consumed during the past
30 days attributable to that brand).
Sample
Knowledge Networks maintains a prerecruited panel of approximately 50,000 adults (including young adults aged 18 to 20) who
have agreed to be invited periodically to participate in Internetbased surveys (Knowledge Networks, 2012). The company recruited
households to its Knowledge Panelâ sample through a combination
of random digit dialing (RDD) and address-based sampling (ABS)
from a sampling frame that includes 97% of U.S. households
(Knowledge Networks, 2012).
To ensure adequate representation of panelists across race/ethnicity, telephone numbers from phone banks with higher concentrations of Blacks and Hispanics are oversampled. To ensure adequate
participation across levels of socioeconomic status, subjects agreeing to participate in the panel who do not have Internet access are
given WebTV and Internet access and training for free.
Using its established Internet panel, Knowledge Networks
recruited youth aged 13 to 17 and young adults aged 18 to 20 via
email to participate in our Internet survey. For the 18- to 20-yearolds, panelists were sent an email invitation that did not indicate the
survey was related to alcohol consumption. Panelists who agreed to
participate in the survey were emailed a link to a secure web site
where a screening questionnaire was administered to determine
whether the panelist consumed alcohol in the past 30 days and was
thus eligible for the survey.
For the 13- to 17-year-olds, respondents were identified by asking
adult panelists to indicate whether they had any children in this age
group and if so, whether they would grant permission to Knowledge
Networks to survey those youth. Only 1 teen was selected—randomly—from each household. If parental consent was given, the
youth was emailed an invitation to participate in the survey.
Based on a screening questionnaire that did not reveal the purpose of the survey, respondents who had consumed at least 1 drink
of alcohol in the past 30 days were provided with an online consent
form. Participants who provided informed consent completed the
Internet-based questionnaire. After completion of the survey, a $25
gift was credited to the panel member’s account. The protocol was
approved by the Institutional Review Board of the Boston University Medical Center.
Response Rate
As the American Association for Public Opinion Research
standards for response rate reporting were not established for
Internet panels, we used a modification of these standards that was
developed and published by Callegaro and Di Sogra (2008). Because
13- to 17-year-olds (younger youth) and 18- to 20-year-olds (older
youth) were recruited differently, we report their response rates
separately.
Because the study involved a screening procedure to determine
eligibility, the overall response rate for the older youth sample
has 2 components: (i) the screening completion rate, which is the
number of completed screenings divided by the total number of
invitations sent; and (ii) the survey completion rate, which is the
number of completed surveys divided by the number of eligible
respondents.
For the younger youth sample, because parents were screened
first to identify potential teenage respondents, the overall response
rate has 3 components: (i) the parent completion rate, which is the
number of parents who confirmed having a teen in their household
and gave consent divided by the estimated number of eligible households with 1 or more teens; (ii) the screening completion rate; and
(3) the survey completion rate.
3
For the older youth sample, the screening completion rate was
46.2% (2,288 invitations, with 1,058 completed screenings). The survey completion rate was 93.8% (705 eligible respondents, with 661
completed surveys). Thus, the overall response rate for the older
youth was 46.2% multiplied by 93.8% or 43.3%.
For the younger youth sample, the parent completion rate was
49.2% (an estimated 4,757 eligible households with 1 or more teens,
with 2,341 parents giving consent). The screening completion rate
was 94.0% (2,341 invitations, with 2,201 teens screened). The survey
completion rate was 95.9% (387 eligible respondents, with 371 completed surveys). Thus, the overall response rate for the younger
youth was 49.2% multiplied by 94.0% multiplied by 95.9% or
44.4%.
Examination of Response Self-Consistency
In an attempt to identify possible errant or implausible reports of
the number of drinks consumed for particular brands, we examined
the self-consistency of the survey responses by comparing the overall number of drinks per day that each respondent reported consuming in the past 30 days to the sum of the number of drinks that
individual reported consuming of each brand. We identified 1 major
inconsistency, in which a respondent reported drinking more than
15 drinks per day of more than 20 alcohol brands. This respondent
was deleted from the data set. Thus, our final data set consisted of
1,031 individuals.
Survey Instrument
The Internet-based survey instrument was developed to assess
brand-specific alcohol consumption among underage youth. Using
several sources, we identified 898 major brands of alcohol within 16
different alcoholic beverage types. The brands included in the data
set consisted of (i) all alcohol brands advertised in national issues of
magazines or on national television (network or cable) during the
years 2006 through 2010, based on data licensed from Nielsen (New
York, 2011), the leading company that tracks advertising placements; (ii) the complete list of alcohol brands measured by GfK
Mediamark Research and Intelligence in its Survey of the Adult
Consumer; (iii) an extensive list of alcoholic energy drinks compiled
by the National Association of Attorneys General; and (iv) all alcohol brands reported by participants in 2 pilot studies of youth alcohol brand preference (Siegel et al., 2011a,b).
The final data set consisted of the following numbers of brands in
each of these categories, with a total of 898 alcohol brands: 306 table
wines, 132 beers, 86 vodkas, 77 cordials/liqueurs, 62 flavored alcoholic beverages, 54 rums, 33 tequilas, 29 whiskeys, 27 gins, 25
scotches, 23 bourbons, 15 brandies, 10 spirits-based energy drinks, 9
cognacs, 5 low-end fortified wines, and 5 grain alcohols.
Our survey was conducted after certain alcoholic energy drinks
were either removed from the market or reformulated so as not to
contain caffeine or other stimulants. Former alcoholic energy drink
brands that remained on the market but without caffeine (e.g., Four
Loko) were classified in our survey as flavored alcoholic beverages.
However, there was a small class of alcoholic energy drinks that
were not removed from the market. These are spirits brands, such as
vodka or liqueur, which contain either caffeine or other stimulants
(e.g., guarana, taurine). Accordingly, we retained them in our survey
under the classification of “spirits-based energy drinks.”
For each category of alcohol, respondents checked off which
specific brands they had consumed during the past 30 days. If a specific brand was not listed, then respondents entered the name, giving
as specific a name as possible. After identifying the brands they had
consumed in the past 30 days, respondents reported the number of
days during the past 30 that they had consumed each brand and
how many drinks of each brand they usually had on a day when
they drank that brand.
SIEGEL ET AL.
4
Drinks were defined based on the NIAAA definition of a “standard drink,” which is a drink size that contains 14 grams of pure
alcohol (National Institute on Alcoholism and Alcohol Abuse
[NIAAA], 2012). Thus, based on the average alcohol content of different alcoholic beverage types, we defined a drink as a 12-ounce
can or bottle of beer; a 5-ounce glass of wine or champagne; 4
ounces of low-end fortified wine; an 8.5-ounce flavored alcoholic
beverage; an 8-ounce alcohol energy drink; a 12-ounce wine cooler;
8.5 ounces of malt liquor; 1.5 ounces of liquor (spirits or hard alcohol), whether in a mixed drink or as a shot; 2.5 ounces of cordials or
liqueurs, whether in a mixed drink, a coffee drink, or consumed on
their own; and 1 ounce of grain alcohol, whether in a mixed drink,
punch, or as a shot.
Measures
Prevalence of Past 30-Day Consumption. The prevalence of past
30-day consumption of each alcohol brand was defined as the proportion of respondents who reported having consumed that brand
in the past 30 days.
Consumption-Based Market Share. The consumption-based
market share for each brand (referred to hereafter simply as “market share”) was defined as the proportion of the total drinks consumed during the past 30 days by all of the respondents combined
that was attributable to a specific brand. To estimate the number of
drinks of each brand consumed in the past 30 days by individual
respondents, we multiplied the number of days they reported drinking that brand by the typical number of drinks of that brand they
reported consuming on those days. The total number of drinks was
then summed across all brands and across all respondents. In calculating market shares, we included drinks for alcoholic beverages
reported as “other” (and not included in our list of 898 brands).
We used a common approach for shielding the analyses of drinking frequency from outlying data without dropping observations:
“winsorization,” which involves recoding outliers at a specified percentile level of the distribution (Balsa et al., 2011; Dixon, 1960).
Winsorization is defined as the replacement of extreme values with a
given, less extreme value. For example, the number of drinks per
day could be recoded from extreme values to a set upper limit
deemed to be reasonable, such as the value at the 99th percentile. In
our data, the 99th percentile for maximum number of drinks per
brand per day was 20. Thus, for each alcohol brand, we winsorized
the reported number of drinks per day at 20. We conducted a sensitivity analysis to examine whether the winsorization procedure
changed our estimates of brand market shares. Differences in estimated market shares were similar with and without winsorization
and the top 25 brands by market share were the same.
Weighting Procedures
Knowledge Networks applied statistical weighting adjustments to
account for selection deviations and to render the sample representative of the underlying population (Di Sogra, 2009). These weights
accounted for the different selection probabilities associated with the
RDD- and ABS-based samples, the oversampling of minority communities, nonresponse to panel recruitment, and panel attrition.
Poststratification adjustments were based on demographic distributions from the Current Population Survey conducted by the U.S.
Bureau of the Census. The poststratification weights adjusted for
gender, age, race/ethnicity, census region, household income, home
ownership status, metropolitan area, and household size.
Validation of Methodology
Validation studies have demonstrated that behavioral data
obtained from the Knowledge Networks panel compare closely with
estimates derived from more traditional survey techniques, such as
national household, telephone, or in-person surveys (Bethell et al.,
2004; Chang and Krosnick, 2009; Heeren et al., 2008; Novak et al.,
2007; Smith, 2003; Yeager et al., 2011). We have previously shown
that estimates of current drinking obtained through a survey
conducted by Knowledge Networks were similar to those from the
National Epidemiologic Survey on Alcohol and Related Conditions
(Heeren et al., 2008). Thus, the Knowledge Networks panel is a less
expensive, viable alternative to telephone and in-person surveys for
assessing drinking behavior.
We initially pilot-tested the survey instrument and assessed its
feasibility and effectiveness among a convenience sample of 241
youth ages 16 to 18 (Siegel et al., 2011b). We then conducted a full
pilot test, using the same methods that are reported in this research,
but restricting the total sample size to 100 completed surveys among
16- to 20-year-olds (Siegel et al., 2011a). We validated our pilot
study results among 18- to 20-year-olds with data on alcohol beverage type preferences among that age group obtained from the 2007
MRI Survey of the Adult Consumer (Siegel et al., 2011a). The concordance of these results demonstrated the validity of our study
methodology in ascertaining type-specific patterns of consumption
among underage youth, thus supporting the use of these methods
for assessing brand-specific alcohol consumption.
Misclassification of Alcohol Brands by Alcoholic Beverage Type
Because we allowed respondents to list “other” brands in each
alcoholic beverage type category, we were able to examine the extent
to which respondents misclassified brands by alcoholic beverage
type. There were a total of 90 misclassifications. Of these, 69 represented misclassifications among categories of beer, spirits, wine, and
flavored alcoholic beverages, and the remaining 21 were misclassifications within types of spirits.
The most common misclassifications were listing flavored alcoholic beverages as alcoholic energy drinks (11 cases involving Four
Loko and Sparks), listing vodkas as flavored alcoholic beverages
(6 cases involving Ciroc, Grey Goose, Skyy, and Smirnoff), listing
Canadian or Irish whiskeys as bourbon (6 cases involving Black
Velvet, Crown Royal, Jameson, Canadian Mist, and Windsor
Canadian), and listing vodkas as beer (4 cases involving Smirnoff,
UV, and Three Olives).
RESULTS
Sample Description
The sample, consisting of 1,031 individuals aged 13 to 20,
was skewed slightly toward women and heavily toward older
adolescents and college-age youth. This was due to the
frequency of drinking, and thus survey eligibility, being
higher among these panelists (Table 1). Distribution of
respondents by race/ethnicity, household income, region,
and Internet access was roughly representative of youth
nationally. Approximately half of the respondents reported
heavy episodic drinking, defined as consuming 5 or more
drinks in a row.
Comparison of Respondents and Nonrespondents
Because the sample of 18- to 20-year-olds was drawn from
the existing Knowledge Networks panelists, we were able to
compare 18- to 20-year-old respondents and nonrespondents
BRAND-SPECIFIC CONSUMPTION OF ALCOHOL
5
Table 1. Demographic Characteristics of Survey Respondents
Number of respondents
Total
1,031
Age
13–15
117
16–18
461
19–20
453
Sex
Male
428
Female
603
Race/ethnicity
White, non-Hispanic
592
Hispanic
214
Black
126
Other
99
Annual household income
Less than $15,000
235
$15,000–$39,999
270
$40,000–$99,999
365
$100,000 or more
161
Region
Northeast
177
Midwest
287
South
327
West
240
Internet access
Yes
934
No
97
Days consumed alcohol in past 30 days
1
295
2–3
308
4–7
207
8 or more
221
Heavy episodic drinking in past 30 days
Yes
512
No
519
Table 2. Comparison of Demographic Characteristics of Older Youth
(Ages 18 to 20) Survey Respondents and Nonrespondents
Percentage (%)
Respondents (%)
100.0
11.4
44.7
43.9
41.5
58.5
57.4
20.8
12.2
9.6
22.8
26.2
35.4
15.6
17.2
27.8
31.7
23.3
90.6
9.4
28.6
29.9
20.1
21.4
49.7
50.3
Internet access refers to access prior to joining the Knowledge Networks
panel. Recruited panelists who did not have Internet access were provided
with access by Knowledge Networks. Heavy episodic drinking is defined
as consuming 5 or more drinks in a row. Proportions in the table are
unweighted.
on basic demographic factors to help assess the nature of
potential nonresponse bias, using a chi-square test to assess
the significance of observed differences (Table 2). The nonrespondents were slightly older (p < 0.05), but similar in gender (p = 0.41). Nonrespondents were more likely to be Black
(p < 0.0001), to come from lower-income households
(p < 0.01), and not to have Internet access (p < 0.0001).
There were no substantial differences by region (p = 0.11).
This type of analysis was not possible for the 13- to 17-yearold nonrespondents.
Total (N)
Age*
18
19
20
Sex
Male
Female
Race/ethnicity*
White, non-Hispanic
Hispanic
Black
Other
Annual household income*
Less than $15,000
$15,000–$39,999
$40,000–$99,999
$100,000 or more
Region
Northeast
Midwest
South
West
Internet access*
Yes
No
Nonrespondents (%)
661
1,274
31.5%
26.2%
42.4%
31.4%
31.0%
37.6%
36.2%
63.8%
38.1%
61.9%
54.8%
22.5%
13.0%
9.7%
43.6%
23.5%
22.2%
10.7%
29.2%
28.6%
30.0%
12.3%
35.5%
30.5%
24.7%
9.3%
15.3%
27.7%
32.5%
24.5%
15.3%
23.6%
37.5%
23.6%
89.4%
10.6%
81.0%
19.0%
Internet access refers to access prior to joining the Knowledge Networks
panel. Recruited panelists who did not have Internet access were provided
with access by Knowledge Networks. Proportions in the table are
unweighted.
*Differences are significant at p < 0.05 by a chi-square test.
(26.3%, 95% CI 21.9 to 30.7%), tequila (21.4%, 95% CI
17.2 to 25.6%), and bourbon (18.4%, 95% CI 14.2 to
22.6%).
The consumption-based market share in the past 30 days
was highest for beer (42.5%), followed by spirits (35.8%),
flavored alcoholic beverages (16.1%), and wine (5.7%)
(Table 3). Among spirits, the top 4 categories by market
share were vodka (11.1%), rum (5.2%), bourbon (4.5%),
and tequila (3.6%). Alcohol brand market shares were concentrated by alcoholic beverage type. The 3 leading types/
subtypes by market share—beer (42.5%), flavored alcoholic
beverages (16.1%), and vodka (11.1%)—accounted for
69.7% of all alcohol drinks consumed. No other alcoholic
beverage type had a market share greater than 5.2%.
Prevalence of Use and Market Share by Brand
Prevalence of Use and Market Share by Alcoholic Beverage
Type
The most prevalent alcoholic beverage types among
underage drinkers were beer (68.9%, 95% confidence interval [CI] 64.4 to 73.3%) and spirits (68.7%, 95% CI 64.4 to
73.0%), followed by flavored alcoholic beverages (49.9%, CI
44.9 to 54.9%) and wine (31.6%, 95% CI 26.9 to 36.3%)
(Table 3). Within the spirits category, the most popular subtypes were vodka (41.5%, 95% CI 36.5 to 46.6%), rum
Examining prevalence of any use in the past 30 days,
the most commonly consumed alcohol brands were Bud
Light (27.9%, 95% CI 23.3 to 32.4%), Smirnoff malt
beverages (17.0%, 95% CI 12.9 to 21.1%), and Budweiser (14.6%, 95% CI 11.0 to 18.3%) (Table 4). Of the top
25 brands, 12 were spirits brands (including 4 vodkas, 3
rums, 2 tequilas, and 1 each of bourbon, cognac, and
cordial/liqueur), 9 were beers, and 4 were flavored alcoholic beverages.
SIEGEL ET AL.
6
Table 3. Prevalence of Alcohol Use and Market Share by Total Number
of Drinks Consumed in the Past 30 Days by Alcoholic Beverage Type
Alcoholic
beverage type
All types
Beer
Flavored alcoholic
beverages
Spirits
Spirits-based energy drinks
Bourbon
Brandy
Cognac
Cordials/Liqueurs
Gin
Rum
Scotch
Tequila
Vodka
Whiskey
Grain alcohol
Wines
Table wine
Low-end fortified wine
Prevalence of
(95% CI) alcohol use
in past 30 days
Market share
by volume
consumed
in past 30 days
100.0%
68.9% (64.4–73.3%)
49.9% (44.9–54.9%)
100.0%
42.5%
16.1%
68.7% (64.4–73.0%)
10.5% (7.2–13.9%)
18.4% (14.2–22.6%)
7.2% (4.6–9.8%)
7.4% (4.4–10.3%)
12.2% (8.9–15.5%)
9.6% (6.8–12.4%)
26.3% (21.9–30.7%)
4.0% (2.0–6.1%)
21.4% (17.2–25.6%)
41.5% (36.5–46.6%)
9.0% (5.9–12.2%)
5.8% (3.3–8.2%)
31.6% (26.9–36.3%)
29.6% (25.0–34.3%)
5.9% (3.9–8.0%)
35.8%
3.3%
4.5%
1.1%
0.8%
2.4%
1.0%
5.2%
0.7%
3.6%
11.1%
1.4%
0.7%
5.7%
5.2%
0.5%
CI, confidence interval. Proportions in the table are weighted. Market
shares represent the total number of drinks in the past 30 days for a given
alcoholic beverage type across the entire sample divided by the total number of drinks for all alcoholic beverage types consumed in the past
30 days. Market share estimates are weighted.
By market share, consumption was concentrated in a
relatively small number of brands, with the top 25 brands
accounting for nearly half of all market share (Table 5).
No other alcohol brands had a market share of 1% or
greater. The leading brands by market share were dominated by beer brands (14), followed by spirits (7: including 3 vodkas, 2 rums, a spirits-based energy drink, and a
bourbon), flavored alcoholic beverage brands (3), and
wine (1).
Table 4. Prevalence of Use in the Past 30 days for the Top 25 Alcohol
Brands
Rank/Brand
1. Bud Light
2. Smirnoff Malt
Beverages
3. Budweiser
4. Smirnoff Vodkas
5. Coors Light
6. Jack Daniel’s
Bourbons
7. Corona Extra
8. Mike’s
9. Captain Morgan
Rums
10. Absolut Vodkas
11. Heineken
12. Bacardi Rums
13. Blue Moon
14. Bacardi Malt
Beverages
15. Jose Cuervo
Tequilas
16. Miller Lite
17. Grey Goose
Vodkas
18. Malibu Rums
19. Four Loko
20. Keystone
Light
21. Hennessy
Cognac
22. Patron
Tequilas
23. Bailey’s Irish
Cream
24. Corona Extra
Light
25. UV Vodkas
Use in past
30 days (95% CI)
Type
ABV
range (%)
27.9% (23.3–32.4%)
17.0% (12.9–21.1%)
Beer
FAB
4.2
5.5–15.0
14.6% (11.0–18.3%)
12.7% (9.2–16.3%)
12.7% (9.2–16.3%)
11.4% (7.9–15.0%)
Beer
Vodka
Beer
Bourbon
5.0
35.0–50.0
4.2
40.0–43.0
11.3% (8.2–14.3%)
10.8% (7.9–13.6%)
10.4% (7.3–13.5%)
Beer
FAB
Rum
4.2–4.6
5.0–10.0
35.0–50.0
10.1% (6.7–13.5%)
9.7% (6.7–12.7%)
9.3% (6.4–12.2%)
8.2% (5.3–11.1%)
8.0% (5.1–11.0%)
Vodka
Beer
Rum
Beer
FAB
40.0–50.0
5.0–5.1
40.0–75.5
5.2–5.6
10.0–15.0
8.0% (5.2–10.8%)
Tequila
40.0
7.4% (4.8–10.1%)
6.7% (4.0–9.5%)
Beer
Vodka
4.2
40.0
6.3% (3.7–8.8%)
6.1% (4.1–8.1%)
6.0% (3.5–8.5%)
Rum
FAB
Beer
21.0–35.0
6.0–12.0
4.2
5.6% (2.8–8.5%)
Cognac
40.0
5.5% (3.2–7.9%)
Tequila
40.0
5.2% (2.7–7.6%)
17.0
5.2% (3.3–7.2%)
Cordials
/Liqueurs
Beer
5.1% (3.1–7.2%)
Vodka
25.0–40.0
3.7–4.6
CI, confidence interval; ABV, alcohol by volume; FAB, flavored alcoholic
beverage. ABV data are taken from the work of DiLoreto and colleagues
(2012). Proportions in the table are weighted.
Natural Light, and Coors Light) accounted for nearly half
(48.2%) of market share.
Market Share by Brand within Alcoholic Beverage Types
Within alcoholic beverage types and subtypes, market
share was concentrated among a small number of brands
(Table 6). For all spirits, the top 18 brands accounted for
half of market share, and the top 34 brands accounted for
two-thirds of market share. Within the rum category, the top
4 brands (Captain Morgan, Bacardi, Malibu, and Admiral
Nelson) accounted for 76.4% of all rum consumption by volume. For tequila, the top 4 brands (Jose Cuervo, Fat Ass,
Patron, and 1800) accounted for 68.0% of market share. For
vodka, the top 4 brands (Grey Goose, Smirnoff, Absolut,
and UV) accounted for 46.8% of market share. For flavored
alcoholic beverages, the top 4 brands (Smirnoff malt beverages, Mike’s, Jack Daniel’s cocktails, and Four Loko)
accounted for 41.7% of market share. Even in a large,
diverse category such as beer, just the top 7 brands (Bud
Light, Budweiser, Coors, Miller Lite, Corona Extra Light,
DISCUSSION
To the best of our knowledge, this is the first comprehensive report of brand-specific alcohol consumption among
underage youth in the United States. Our major finding is
that although alcohol consumption is spread out over a considerable number of alcoholic beverage types, it is concentrated among a relatively small number of alcohol brands.
The top 25 brands account for about half of all alcohol consumption by volume. Within alcoholic beverage types and
subtypes, a small number of brands account for an even larger proportion of the alcohol consumed.
The most important limitation of this study is that the
response rates of 43% among 18- to 20-year-olds and 44%
among 13- to 17-year-olds create the possibility of nonresponse bias, a form of selection bias. Based on a comparison
of respondents and nonrespondents, the primary concern is
BRAND-SPECIFIC CONSUMPTION OF ALCOHOL
7
Table 5. Consumption-Based Market Shares in the Past 30 Days for the
Top 25 Alcohol Brands
Rank/Brand
1. Bud Light
2. Budweiser
3. Smirnoff Malt
Beverages
4. Coors
5. Miller Lite
6. Corona Extra Light
7. Natural Light
8. Coors Light
9. Corona Extra
10. Keystone Light
11. Mike’s
12. Grey Goose
Vodkas
13. Heineken
14. Natural Ice
15. Jack Daniel’s
Bourbon
16. Guinness
17. Captain Morgan
Rums
18. Agwa de Bolivia
19. Smirnoff Vodkas
20. Barefoot Wines
21. Czechvar
22. Absolut Vodkas
23. Bacardi Rums
24. Blue Moon
25. Jack Daniel’s
Cocktails
Market
share (%)
Cumulative
market share (%)
Beer
Beer
FAB
6.4
3.0
2.9
6.4
9.3
12.2
Beer
Beer
Beer
Beer
Beer
Beer
Beer
FAB
Vodka
2.6
2.3
2.2
2.1
2.0
2.0
2.0
1.9
1.8
14.9
17.1
19.4
21.4
23.4
25.4
27.3
29.3
31.0
Beer
Beer
Bourbon
1.8
1.6
1.6
32.8
34.4
36.0
Beers
Rum
1.5
1.4
37.5
38.9
SED
Vodka
Wine
Beer
Vodka
Rum
Beer
FAB
1.4
1.4
1.3
1.3
1.3
1.3
1.0
1.0
40.4
41.7
43.1
44.4
45.6
46.9
47.9
48.9
Type
SED, spirits-based energy drink; FAB, flavored alcoholic beverage. Market share represents the total number of drinks in the past 30 days for a
given brand across the entire sample divided by the total number of drinks
in the past 30 days for all brands. All market share estimates in the table
are weighted.
that both Black and lower-income youth were less likely
to have responded. To reduce the potential for nonresponse bias, we adjusted our estimates, via poststratification, by weighting the survey responses from Black and
lower-income respondents more heavily. Note that, as our
aim was to assess differences in alcohol brand use rather
than absolute rates of alcohol use in the population, bias
would be introduced only if nonrespondents had differential brand preferences. Even with this weighting procedure,
differential response bias remains a possibility, and these
results should therefore be interpreted with caution.
In particular, a potential concern is that nonresponse bias
led to an underrepresentation of Black and lower-income
respondents in the survey, meaning that our estimates of
brand consumption prevalence and market shares may be
biased toward White, middle- and upper-income youth.
Although beyond the scope of this article, we plan to examine and report demographic differences in alcohol brand
preference in a subsequent article. This will help public
health practitioners understand brand-specific drinking patterns that are relevant to the particular communities in which
they work.
Table 6. Consumption-Based Market Shares within Category in the Past
30 Days for the Top 5 Brands in Each of the 6 Most Popular Alcoholic
Beverage Categories
Type (absolute market
share) Rank Brand (absolute
market share)
Market share with
in category (%)
Beer (42.5%)
1. Bud Light (6.4%)
2. Budweiser (3.0%)
3. Coors (2.6%)
4. Miller Lite (2.3%)
5. Corona Light (2.2%)
Flavored alcoholic beverages (16.1%)
1. Smirnoff Malt
Beverages (2.9%)
2. Mike’s (1.9%)
3. Jack Daniel’s
Cocktails (1.0%)
4. Four Loko (0.9%)
5. Bacardi Malt
Beverages (0.9%)
Vodka (11.1%)
1. Grey Goose (1.8%)
2. Smirnoff (1.4%)
3. Absolut (1.3%)
4. UV (0.8%)
5. Pinnacle (0.6%)
Wine (5.7%)
1. Barefoot (1.3%)
2. Arbor Mist (0.4%)
3. Wild Vines (0.3%)
4. Franzia (0.2%)
5. Sutter Home (0.2%)
Rum (5.2%)
1. Captain Morgan (1.4%)
2. Bacardi (1.3%)
3. Malibu (0.7%)
4. Admiral Nelson’s (0.6%)
5. Coconut Jack (0.2%)
Bourbon (4.5%)
1. Jack Daniel’s (1.6%)
2. Wild Turkey (0.9%)
3. Jim Beam (0.7%)
4. Jeremiah Weed (0.3%)
5. Firefly (0.3%)
Tequila (3.6%)
1. Jose Cuervo (0.9%)
2. Fat Ass (0.7%)
3. Patron (0.6%)
4. 1800 (0.3%)
5. El Jimador (0.3%)
Cumulative market
share within
category (%)
15.0
7.0
6.2
5.4
5.2
15.0
22.0
28.2
33.6
38.8
18.0
18.0
11.9
6.2
29.9
36.1
5.6
5.3
41.7
47.0
15.9
12.2
11.5
7.2
5.5
15.9
28.1
39.6
46.8
52.3
25.7
6.8
5.5
4.7
4.7
25.7
32.5
38.0
42.7
47.4
27.9
24.2
13.2
11.1
3.7
27.9
52.1
65.3
76.4
80.1
35.0
19.0
14.8
7.3
6.8
35.0
54.0
68.8
76.1
82.9
24.4
18.2
16.4
9.0
8.6
24.4
42.6
59.0
68.0
76.6
Market share represents the total number of drinks in the past 30 days
for a given brand across the entire sample divided by the total number of
drinks in the past 30 days for all brands in that alcoholic beverage category. All market share estimates in the table are weighted.
While nonresponse bias could potentially limit the generalizability of these findings to some population subgroups, it
does not threaten the validity of our basic finding that underage alcohol use is concentrated among a relatively small
number of brands. This finding is important for 3 reasons.
First, it suggests that research examining the relationship
between brand-specific advertising exposure among youth,
and their alcohol brand preferences could provide important
insights into the influence of advertising on youth drinking
behavior. Now that we have identified underage youth
SIEGEL ET AL.
8
consumption levels for a wide range of alcohol brands, the
logical next step is to examine the relationship between
underage drinkers’ exposure to brand-specific alcohol advertising and their brand-specific consumption patterns. The
clear demarcation between a small number of brands that
are popular among youth and a much larger number of
brands that are not consumed by youth makes it possible to
examine whether the brands with the highest youth advertising exposure are also the ones preferred and consumed by
youth drinkers. Similar research that studied the relationship
between brand-specific cigarette advertising and cigarette
brand market shares among youth played a central role in
elucidating the influence of cigarette advertising on youth
smoking behavior (King and Siegel, 1999; King et al., 1998;
Pollay et al., 1996).
Second, the finding that alcohol use is concentrated among
a relatively small number of brands has implications for public health practice. Alcohol prevention programs and policies
can now target specific brands, and advocacy efforts can
focus on specific companies that manufacture the products
most involved in problem drinking behavior among youth.
Third, these results suggest that it may be feasible for federal agencies or public health organizations to establish a
surveillance system to monitor alcohol brand use among
underage drinkers. Although there are hundreds of alcohol
brands, monitoring just the top 100 brands would capture
nearly 80% of all underage youth alcohol consumption, and
just the top 25 brands would capture nearly 50% of underage
consumption. Note that the Monitoring the Future survey
includes 23 cigarette brands.
Our finding that youth liquor preferences are highly
concentrated among a small number of brands contrasts
with adult brand consumption. While half of all spirits
market share among underage drinkers is accounted for
by 18 brands, 50% of the overall spirits market share in
the United States in 2010 was accounted for by 33 brands
(Impact Databank, 2011). While two-thirds of the spirits
market share among underage youth is accounted for by
34 brands, the same proportion of overall spirits market
share in 2010 was accounted for by 65 brands (Impact
Databank, 2011).
Another important finding of this study is that underage
youth widely misclassify brands by alcoholic beverage type.
Among 198 youth who reported an “other” brand that was
not included in a list of brands for a given type in the survey,
there were 90 misclassifications. This finding suggests that
previous studies that asked youth to report their consumption of alcoholic beverage categories (beer, spirits, flavored
alcoholic beverages, etc.) may be inaccurate.
Despite potential limitations, these survey data are valuable, as they are the first available national estimates of
youth alcohol brand preference that describe brand-specific
alcohol use among underage drinkers. Our hope is that this
work, by elucidating the nature and extent of alcohol
consumption among underage drinkers and by providing a
feasible and affordable methodology for its measurement,
will inspire other attempts to measure youth alcohol brand
preferences and further research on underage alcohol consumption.
ACKNOWLEDGMENTS
This research was supported by a grant from the National
Institute on Alcohol Abuse and Alcoholism (R01
AA020309-01). CK gratefully acknowledges additional support from Pleiades Consulting Group, Inc.
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